Sensitivity of estimands in clinical trials with imperfect compliance

Chen Heng () and Heitjan Daniel F. ()
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Chen Heng: Biostatistics, Gilead Sciences Inc., Foster City, CA 94404, USA
Heitjan Daniel F.: Department of Statistical Science, Southern Methodist University, Dallas, TX 75205, USA

The International Journal of Biostatistics, 2024, vol. 20, issue 1, 57-67

Abstract: In clinical trials that are subject to noncompliance, the commonly used intention-to-treat estimand is valid as a causal effect of treatment assignment but is sensitive to the level of compliance. An alternative estimand, the complier average causal effect (CACE), measures the average effect of treatment received in the latent subset of subjects who would comply with either assigned treatment. Because the principal stratum of compliers can vary with the circumstances of the trial, CACE too depends on the compliance fraction. We propose a model in which an underlying latent proto-compliance interacts with trial characteristics to determine a subject’s compliance behavior. When the latent compliance is independent of the individual treatment effect, the average causal effect is constant across compliance classes, and CACE is robust across trials and equal to the population average causal effect. We demonstrate the potential degree of sensitivity of CACE in a simulation study, an analysis of data from a trial of vitamin A supplementation in children, and a meta-analysis of trials of epidural analgesia in labor.

Keywords: complier average causal effect; intention-to-treat; noncompliance; randomization; sensitivity (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1515/ijb-2022-0105

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